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1 Ergebnisse
1
34.2 A 16nm 96Kb Integer/Floating-Point Dual-Mode-Gain-Cell..:
, In:
2024 IEEE International Solid-State Circuits Conference (ISSCC)
,
Khwa, Win-San
;
Wu, Ping-Chun
;
Wu, Jui-Jen
... - p. 568-570 , 2024
Link:
https://doi.org/10.1109/ISSCC49657.2024.10454447
RT T1 <cTitle>2024 IEEE International Solid-State Circuits Conference (ISSCC)</cTitle>: T1 <Title>34.2 A 16nm 96Kb Integer/Floating-Point Dual-Mode-Gain-Cell-Computing-in-Memory Macro Achieving 73.3-163.3TOPS/W and 33.2-91.2TFLOPS/W for AI-Edge Devices</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10454447&Exemplar=1&LAN=DE A1 Khwa, Win-San A1 Wu, Ping-Chun A1 Wu, Jui-Jen A1 Su, Jian-Wei A1 Chen, Ho-Yu A1 Ke, Zhao-En A1 Chiu, Ting-Chien A1 Hsu, Jun-Ming A1 Cheng, Chiao-Yen A1 Chen, Yu-Chen A1 Lo, Chung-Chuan A1 Liu, Ren-Shuo A1 Hsieh, Chih-Cheng A1 Tang, Kea-Tiong A1 Chang, Meng-Fan YR 2024 SN 2376-8606 K1 Artificial neural networks K1 In-memory computing K1 Data transfer K1 Common Information Model (computing) K1 Computational efficiency K1 Solid state circuits K1 Arrays SP 568 OP 570 LK http://dx.doi.org/https://doi.org/10.1109/ISSCC49657.2024.10454447 DO https://doi.org/10.1109/ISSCC49657.2024.10454447 SF ELIB - SuUB Bremen
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